Current MS Students/Jerry Chang

From CSWiki

Feature Tracking and Registration in Video

Contents 1 What I am planning to accomplish 1.1 (Project) Brief Project specification 1.2 (Project) High level architecture 1.3 (Thesis) Issues to be investigated 1.4 (Thesis) Annotated table of contents 2 Why this is academically interesting 2.1 Intended audience 2.2 Why this is MS-level work 3 Previous work 3.1 Literature review 3.2 (Project) Platforms to be used and what I will add to each 3.3 (Project) Available platforms I am not using and why 4 Anticipated challenge(s) 4.1 Challenge(s) 4.2 Anticipated approach to each challenge 5 What I bring to this work 5.1 My relevant background and experience (CS 590) 5.2 What I find interesting about this work 5.3 How this work goes beyond my experience and course work

[edit] What I am planning to accomplish

[edit] (Project) Brief Project specification

Develop software to analyze video streams by detecting and tracking features throughout the video, including features that disappear from a scene due to motion. The resulting set of features can then be utilized for higher level applications. Once the software is complete, write a paper that describes the methods implemented by the software.

[edit] (Project) High level architecture

The project will be a standalone application that will produce a video where global features are visually tracked and displayed. In order to be used by other applications, the code can be compiled as a library.

[edit] (Thesis) Issues to be investigated

Results of experiments on feature tracking and performance as discovered by working on the software.

[edit] (Thesis) Annotated table of contents

[edit] Why this is academically interesting

[edit] Intended audience

Developers who want to make use of feature and object detection/tracking in their applications.

[edit] Why this is MS-level work

Video registration is a field in which there is no current "best" approach, meaning research is still ongoing. The goal of this project is to try a new approach and evaluate its performance.

[edit] Previous work

[edit] Literature review

• Lowe, D. G., “Distinctive Image Features from Scale-Invariant Keypoints”, International Journal of Computer Vision, 60, 2, 2004.
  • Lowe's paper on SIFT, discussing the algorithm and theory behind how it works. A longer summary will be added here in time.
• Improved Video Registration using Non-Distinctive Local Image Features, Robin Hess and Alan Fern, In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.

[edit] (Project) Platforms to be used and what I will add to each

• OpenCV - a widely-used open source library designed for computer vision applications. Using OpenCV will simplify the task of programming by providing implementations for common CV operations.

[edit] (Project) Available platforms I am not using and why

[edit] Anticipated challenge(s)

[edit] Challenge(s)

[edit] Anticipated approach to each challenge

[edit] What I bring to this work

[edit] My relevant background and experience (CS 590)

I took both CS 451 (Multimedia Software Systems) and CS 560 (Advanced Topics in Artificial Intelligence, covering computer vision), which gave me enough of a basic background to get into this topic.

[edit] What I find interesting about this work

Video registration is still an area that will require a large amount of research, and yet fundamental enough such that it is useful in a wide variety of applications.

[edit] How this work goes beyond my experience and course work

Course work usually involves clear specifications and gives students a way to implement those specifications. In this project, I have to evaluate different ways of accomplishing the goal, but there is no set method or guideline to follow, nor are good results guaranteed.